A novel dynamic neural network structure for nonlinear system identification
A novel dynamic neural network structure for nonlinear system identification
复制标题
一种用于非线性系统辨识的新型动态神经网络结构
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
S. Nasuto
中科院分区：
文献类型：
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作者：
Jiamei Deng;V. Becerra;S. Nasuto
动态神经网络常用于非线性系统辨识。提出了一种适用于非线性系统辨识的串并联动态神经网络结构。理论证明表明，这种类型的动态神经网络能够逼近非线性动力系统的有限轨迹。并对一个实际的三维非线性起重机系统进行了训练。
Dynamic neural networks are often used for nonlinear system identification. This paper presents a novel series-parallel dynamic neural network structure which is suitable for nonlinear system identification. A theoretical proof is given showing that this type of dynamic neural network is able to approximate finite trajectories of nonlinear dynamical systems. Also, this neural network is trained to identify a practical nonlinear 3D crane system.